Effects of charge and hydrophobicity on the oligomerization of peptides derived from IAPP

Changes in pH resulting in modifications of charge can dramatically alter the folding and interaction of proteins. This article probes the effects of charge and hydrophobicity on the oligomerization of macrocyclic β-sheet peptides derived from residues 11–17 of IAPP (RLANFLV). Previous studies have shown that a macrocyclic β-sheet peptide containing this IAPP sequence (peptide 1_Arg) does not form oligomers in aqueous solution at low millimolar concentrations. Replacing arginine with the uncharged isostere citrulline generates a homologue (peptide 1_Cit) that forms a tetramer consisting of a sandwich of hydrogen-bonded dimers. The current study probes the role of charge and hydrophobicity by changing residue 11 to glutamic acid (peptide 1_Glu) and leucine (peptide 1_Leu). Diffusion-ordered spectroscopy (DOSY) studies show that peptides 1_Glu and 1_Leu form tetramers in solution. NOESY studies confirm that both peptides form the same sandwich-like tetramer as peptide 1_Cit. ¹H NMR spectroscopy at various concentrations reveals that peptide 1_Leu has the highest propensity to form tetramers. The effects of pH and charge on oligomerization are further probed by incorporating histidine at position 11 (peptide 1_His). DOSY studies show that peptide 1_His forms a tetramer at high pH. At low pH, peptide 1_His forms a new species that has not been previously observed by our research group—a dimer. These studies demonstrate the importance of charge and hydrophobicity in the oligomerization of IAPP-derived peptides.     

Pitfalls in the statistical analysis of microbiome amplicon sequencing data

Microbiome data are characterized by several aspects that make them challenging to analyse statistically: they are compositional, high dimensional and rich in zeros. A large array of statistical methods exist to analyse these data. Some are borrowed from other fields, such as ecology or RNA-sequencing, while others are custom-made for microbiome data. The large range of available methods, and which is continuously expanding, means that researchers have to invest considerable effort in choosing what method(s) to apply. In this paper we list 14 statistical methods or approaches that we think should be generally avoided. In several cases this is because we believe the assumptions behind the method are unlikely to be met for microbiome data. In other cases we see methods that are used in ways they are not intended to be used. We believe researchers would be helped by more critical evaluations of existing methods, as not all methods in use are suitable or have been sufficiently reviewed. We hope this paper contributes to a critical discussion on what methods are appropriate to use in the analysis of microbiome data.     

A new genus and species of the rove beetle tribe Mesoporini from Baltic amber (Coleoptera: Staphylinidae: Aleocharinae)

A new extinct rove beetle, Palaeomesoporus electiricus gen. et sp.n., is described from a single specimen of Eocene Baltic amber. This fossil beetle is placed in the tribe Mesoporini, a ‘basal’ group of the mega-diverse subfamily Aleocharinae. Palaeomesoporus is easily discriminated from other mesoporine genera due to its less-developed antennal club, longer and slender elytron lacking a sinuate posterior margin, and prominently shorter mesotarsus. This finding sheds light on the paleodiversity and evolutionary history of the tribe and ‘basal’ Aleocharinae.     

Cytotoxic tetraoxygenated xanthones from the bark of Garcinia schomburgkiana

Two new tetraoxygenated xanthones, 6-O-demethyloliverixanthone and schomburgxanthone, together with cowanin, cowanol, fuscaxanthones A and B, 3-isomangostin hydrate, and 1,7-dihydroxyxanthone, were isolated from the bark of Garcinia schomburgkiana. Their structures were elucidated using 1-D and 2-D NMR techniques as well as chemical methods. Five of the isolated compounds were tested regarding their cytotoxicity against HeLa cells and the results showed that fuscaxanthone B and cowanin possessed remarkable activity with IC₅₀ values of 2.4 ± 0.2 and 2.7 ± 0.3 μg/ml, respectively, using an MTT assay.     

Diversity of pselaphine beetles (Coleoptera: Staphylinidae: Pselaphinae) in eastern Thailand

Pselaphine beetles (Coleoptera: Staphylinidae: Pselaphinae) are cosmopolitan, species‐rich, and yet poorly studied, particularly in the tropics. We sampled beetles in three types of primary forest and two types of disturbed forest habitats in eastern Thailand to assess the utility of pselaphine beetles as bioindicators of forest disturbance. We simultaneously measured leaf litter mass, soil moisture, soil acidity and canopy cover at each site to infer which environmental factors affect pselaphine beetle diversity and abundance. At each site, pselaphine beetles were extracted from ten 1 m² samples of leaf litter and soil with Tullgren funnels. We sampled 1867 adult beetles representing six supertribes, 51 genera and 114 morphospecies; 7% of the genera and 92% of the species were undescribed. Forest types differed significantly in species richness, abundance, diversity and evenness. Primary forest had greater numbers of species and individuals, and higher diversity indices (H′). Teak plantation and secondary forest had substantially fewer individuals and species of pselaphine beetles. Species composition differed between primary and degraded forests. Canopy cover, soil moisture, and leaf litter mass positively correlated with beetle species richness and abundance. Leaf litter mass and soil moisture were the two most important factors affecting the diversity of pselaphine beetle assemblages. Among the 114 morphospecies collected, 43 morphospecies were specific to two or three habitats and 64 morphospecies were found only in a single habitat. Thus pselaphine beetles appear to have rather narrow habitat requirements and their presence/absence was correlated with environmental differences. These traits make pselaphine beetles a suitable bioindicator taxon for assessing forest litter diversity and monitoring habitat change.     

Linkage analysis by two-dimensional DNA typing.

In two-dimensional (2-D) DNA typing, genomic DNA fragments are separated, first according to size by electrophoresis in a neutral polyacrylamide gel and second according to sequence by denaturing gradient gel electrophoresis, followed by hybridization analysis using micro- and minisatellite core probes. The 2-D DNA typing method generates a large amount of information on polymorphic loci per gel. Here we demonstrate the potential usefulness of 2-D DNA typing in an empirical linkage study on the red factor in cattle, and we show an example of the 2-D DNA typing analysis of a human pedigree. The power efficiency of 2-D DNA typing in general is compared with that of single-locus typing by simulation. The results indicate that, although 2-D DNA typing is very efficient in generating data on polymorphic loci, its power to detect linkage is lower than single-locus typing, because it is not obvious whether a spot represents the presence of one or two alleles. It is possible to compensate for this lower informativeness by increasing the sample size. Genome scanning by 2-D DNA typing has the potential to be more efficient than current genotyping methods in scoring polymorphic loci. Hence, it could become a method of choice in mapping genetic traits in humans and animals.     

Reconstruction and functional characterization of the human mitochondrial metabolic network based on proteomic and biochemical data

Diverse datasets including genomic, proteomic, isotopomer, and DNA sequence variation are becoming available for human mitochondria. Thus there is a need to integrate these data within an in silico modeling framework where mitochondrial biology and related disorders can be studied and analyzed. This paper reports a reconstruction and characterization of the human mitochondrial metabolic network based on proteomic and biochemical data. The 189 reactions included in this reconstruction are both elementally and charge-balanced and are assigned to their respective cellular compartments (mitochondrial, cytosol, or extracellular). The capabilities of the reconstructed network to fulfill three metabolic functions (ATP production, heme synthesis, and mixed phospholipid synthesis) were determined. Network-based analysis of the mitochondrial energy conversion process showed that the overall ATP yield per glucose is 31.5. Network flexibility, characterized by allowable variation in reaction fluxes, was evaluated using flux variability analysis and analysis of all of the possible optimal flux distributions. Results showed that the network has high flexibility for the biosynthesis of heme and phospholipids but modest flexibility for maximal ATP production. A subset of all of the optimal network flux distributions, computed with respect to the three metabolic functions individually, was found to be highly correlated, suggesting that this set may contain physiological meaningful fluxes. Examinations of optimal flux distributions also identified correlated reaction sets that form functional modules in the network.